Knowledge is an important resource for business organizations. It is constantly being generated as a result of the continuous accumulation of information, and its use by an organization. Knowledge bases are used to store the generated knowledge.
Knowledge bases need regular maintenance, as knowledge is not a static resource. Fresh insights, changing business requirements, alternative or external resources and acquired experiences have to be constantly incorporated to the existing knowledge.
To this end, usually there are knowledge engineers who are assigned the task of maintaining and updating knowledge bases. Maintaining a structured knowledge base involves searching through the knowledge base to match the knowledge present in the knowledge base with knowledge obtained from interviews with experts. This is an economically unviable and manually intensive process. Knowledge engineers have to depend completely on the experts to determine whether any information is missing, or any discrepancies exist in the knowledge base, and to provide them with the necessary information.
Another problem that knowledge engineers face is the task of classifying the information that they obtain through interviews with experts, for incorporation into the knowledge base. Known techniques fail to appreciate and effectively address these concerns.
Accordingly, the present invention addresses the abovementioned problems and others.